Pipeline systems are an integral component of global energy distribution. There are more than 2.6 million miles of energy pipelines in the United States alone, delivering trillions of cubic feet of natural gas and hundreds of billions of ton/miles of liquid petroleum products each year. To ensure the safety of these vast pipeline systems and often to comply with governmental regulations, pipeline operators must frequently service their pipelines and perform periodic inspections to assess pipeline integrity. Mechanical devices referred to as pipeline inspection gauges (or “pigs”) are often employed to perform these maintenance and inspection functions inside the pipeline.
There are generally two types of pigs used to perform in-line maintenance operations: cleaning pigs and instrumented or smart pigs. Cleaning pigs are often purely mechanical devices that that clean the inside of the pipeline by performing various cleaning functions such as brushing, scraping, or polishing along the inside wall surfaces to remove debris as the pigs are pushed through the pipeline by the pressure of the product in the pipeline. Smart pigs are instrumented, electromechanical devices often referred to as in-line-inspection (ILI) tools that are used to inspect the pipeline for corrosion, metal loss, deformations, and the position of the pipeline. The different types of smart pigs are characterized by the different types of technologies implemented to perform their inspection functions. Ultrasonic transducing (UT) pigs use sound waves to measure the thickness of the wall of a steel pipe. A UT pig calculates the thickness of the wall based on the speed of sound in steel. Curvature detection pigs employ inertial navigation technology to measure the position and shape of the pipe.
Another type of smart pig is a magnetic flux leakage (MFL) detection pig. MFL pigs use powerful magnets to saturate the pipe wall with magnetism and then carry out a corrosion measurement function. Sensors between the poles of the magnets detect disturbances caused by metal loss due to corrosion or other mechanical damage. MFL pigs, like many smart pigs, are typically separated into sections or packages that house specific instrumentation or carry out specific functions. For instance, an MFL pig can include a drive package for propulsion, a sensor package for carrying out signal detection for corrosion measurements, a navigational package for determining relative or global position, and a power package for powering any on-board electronics. The packages are tethered to one another via flexible joints that allow the respective packages to pass individually through bends in the pipe.
FIG. 15 depicts a sensor package 400 of a prior art MFL pig. The sensor package 400 typically has sensors (not shown) affixed to or embedded in flexible arms 402 that touch the inside surface of a pipe as the pig moves axially along the pipe in the product flow direction. The flexible arms 402 are mounted on a body 404 of the MFL pig and circumferentially spaced about a central axis 12 defined by the body 404 so that the sensors detect magnetic flux leakage through an entire cross section of the pipe at one time. The arms 402 flex in a radial direction 16 generally perpendicular to the central axis 12 to accommodate reductions or other diametric anomalies in the pipe as the MFL pig is propelled through the pipe.
The algorithms used to process the magnetic flux leakage detected by the sensor depend on certain assumptions about the physical position of the sensors. Namely, the algorithms assume that the circumferential spacing between each pair of adjacent arms and, therefore, each pair of adjacent sensors is approximately equal for any given radial position of the arms within the pipeline. In practice, however, the dynamics of the MFL pig as it moves through the pipeline along with variances in pipeline diameter and debris existing in the pipeline cause variable spacing between the adjacent pairs of sensors on the MFL pig.
This variable spacing, in turn, makes data interpretation less reliable. For instance, assume that one sensor is affixed to each flexible arm of the MFL pig and the defect sizing algorithm assumes that the spacing between adjacent sensors for a given radial position of the arms based on the design of the MFL pig is 0.250 inches. If the actual spacing between two adjacent sensors is 0.320 inches because one arm is unexpectedly displaced from its intended neutral position, then the calculation of the size of the defect that is detected by these two adjacent sensors can be off by plus or minus 0.070 inches.
Accordingly, it would be advantageous to maintain the spacing between adjacent sensors in MFL pigs for any given radial position of the arms in order to improve the reliability of pipeline defect size estimations based on data acquired from such MFL pigs.